Tag: observations
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Weighted MCC: A Robust Measure of Multiclass Classifier Performance for Observations with Individual Weights
Weighted MCC: A Robust Measure of Multiclass Classifier Performance for Observations with Individual Weights arXiv:2512.20811v1 Announce Type: new Abstract: Several performance measures are used to evaluate binary and multiclass classification tasks. But individual observations may often have distinct weights, and none of these measures are sensitive to such varying weights. We propose a new weighted…
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Symmetric Linear Dynamical Systems are Learnable from Few Observations
Symmetric Linear Dynamical Systems are Learnable from Few Observations arXiv:2512.05337v1 Announce Type: new Abstract: We consider the problem of learning the parameters of a $N$-dimensional stochastic linear dynamics under both full and partial observations from a single trajectory of time $T$. We introduce and analyze a new estimator that achieves a small maximum element-wise error…
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An Exponential Averaging Process with Strong Convergence Properties
An Exponential Averaging Process with Strong Convergence Properties arXiv:2505.10605v1 Announce Type: new Abstract: Averaging, or smoothing, is a fundamental approach to obtain stable, de-noised estimates from noisy observations. In certain scenarios, observations made along trajectories of random dynamical systems are of particular interest. One popular smoothing technique for such a scenario is exponential moving averaging…
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On Generalization and Distributional Update for Mimicking Observations with Adequate Exploration
On Generalization and Distributional Update for Mimicking Observations with Adequate Exploration arXiv:2501.12785v1 Announce Type: new Abstract: This paper tackles the efficiency and stability issues in learning from observations (LfO). We commence by investigating how reward functions and policies generalize in LfO. Subsequently, the built-in reinforcement learning (RL) approach in generative adversarial imitation from observation (GAIfO)…